WO2021184413A1 - Biomarqueurs à base de microbes intestinaux pour prédire un effet curatif sur un trouble bipolaire, et criblage et applications de ceux-ci - Google Patents

Biomarqueurs à base de microbes intestinaux pour prédire un effet curatif sur un trouble bipolaire, et criblage et applications de ceux-ci Download PDF

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WO2021184413A1
WO2021184413A1 PCT/CN2020/081945 CN2020081945W WO2021184413A1 WO 2021184413 A1 WO2021184413 A1 WO 2021184413A1 CN 2020081945 W CN2020081945 W CN 2020081945W WO 2021184413 A1 WO2021184413 A1 WO 2021184413A1
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bipolar disorder
treatment
biomarker
patients
relative abundance
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PCT/CN2020/081945
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Chinese (zh)
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胡少华
张佩芬
来建波
蒋佳俊
许毅
奚彩曦
杜彦莉
吴玲玲
路静
牟婷婷
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浙江大学
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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/004—Artificial life, i.e. computing arrangements simulating life
    • G06N3/006—Artificial life, i.e. computing arrangements simulating life based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B30/00—ICT specially adapted for sequence analysis involving nucleotides or amino acids

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  • the invention relates to an intestinal microbial marker for predicting the curative effect of bipolar disorder and its screening application.
  • Bipolar disorder is a type of chronic mental illness with alternating or mixed depression, mania, or hypomania as the main clinical features.
  • the etiology is unknown.
  • the age of onset is mainly concentrated in early adulthood or late adolescence.
  • the global incidence is high, about 2 to 3%, related to obvious damage to occupational, personal and social functions, and accompanied by physical diseases and early death.
  • the treatment of bipolar disorder is mainly based on drug therapy, supplemented by the comprehensive treatment principle of physical therapy and psychotherapy. Even after treatment, residual emotional symptoms often still exist. About 37% of patients relapse as depression or mania within 1 year, and 60% of patients relapse within 2 years. Repeated attacks for many times severely damage the brain function of patients, prolong the time of drug treatment, and reduce the effectiveness of treatment.
  • bipolar disorder is the result of the interaction of genetic factors and environmental factors, and changes in the nervous, immune, and endocrine systems are also shown to varying degrees, it is aimed at the early stage of the treatment of bipolar disorder. It is predicted that there is still a lack of specific biomarkers.
  • the purpose of the present invention is to provide gut microbial markers for predicting the curative effect of bipolar disorder and their screening applications.
  • Biomarkers for predicting the efficacy of bipolar disorder based on gut microbes including many of the following 6 types: “Bacteroides_clarus”, “Eubacterium_biforme”, “Weissella_confusa”, “Ruminococcus_torques”, “Bifidobacterium_dentium”, “Collinsella_unclassified” in bipolar
  • biomarkers for predicting the efficacy of bipolar disorder based on gut microbes including many of the following 6 types: “Bacteroides_clarus”, “Eubacterium_biforme”, “Weissella_confusa”, “Ruminococcus_torques”, “Bifidobacterium_dentium”, “Collinsella_unclassified” in bipolar
  • the biomarkers are the following three types:
  • Biomarker 1 Eubacterium_biforme; importance 0.15259;
  • Biomarker 2 Ruminococcus_torques; importance 0.339395;
  • the relative abundance of the above-mentioned biomarker combination in the treatment-effective group of patients with bipolar disorder is significantly increased.
  • the biomarkers are provided based on the calculation of their gene sequences.
  • the relative abundance information of the biomarkers is used for comparison with reference values.
  • a screening method based on the biomarker the steps are as follows:
  • Sample collection Collect samples of subjects including fecal samples from patients with bipolar disorder before treatment, and store them in the refrigerator at -80°C for later use;
  • the described screening method further uses the random forest model to predict and analyze, and the steps are as follows:
  • the treatment-effective group and the treatment-ineffective group of patients with bipolar disorder are the training set, and the remaining samples are used as the test set, and the relative abundance of the species in each sample in the training set is calculated;
  • the sample subjects included 27 patients with effective treatment of bipolar disorder and 14 patients with ineffective treatment, and in the test set, the sample subjects included 8 patients with effective treatment of bipolar disorder and 5 patients with ineffective treatment.
  • the present invention analyzes the intestinal flora and gene sequence of the effective and ineffective groups of patients with bipolar disorder to screen out biomarkers that are highly correlated with the curative effect of bipolar disorder, and use the markers It can accurately predict the curative effect of bipolar disorder and monitor the treatment effect.
  • the response of the relevant biomarkers of patients with bipolar disorder proposed in the present invention to the therapeutic effect is valuable.
  • stool sample extraction is portable and non-invasive, which can increase patient compliance. at the same time.
  • stool samples are transportable, and sample analysis is accurate and safe.
  • the markers of the present invention have high specificity and sensitivity, and can be used for the prediction of therapeutic efficacy.
  • Fig. 1 shows the difference in the relative abundance of the flora between the treatment-effective group and the treatment-ineffective group of patients with bipolar disorder at the species level according to an embodiment of the present invention.
  • the diagram shows that there is a significant difference in the relative abundance of the bacterial flora in the treatment-effective group and the treatment-ineffective group in patients with bipolar disorder.
  • Fig. 2 shows the error rate distribution of the classifier for 5 times of 10-fold cross-validation according to an embodiment of the present invention.
  • Fig. 3 is based on a random forest model (3 gut markers) according to an embodiment of the present invention, and the receiver operating characteristic (Receiver Operating Characteristic, ROC) curve and the area under the curve (Area under Curve, AUC).
  • ROC Receiveiver Operating Characteristic
  • Figure 4 shows the receiver operating characteristic ROC curve and curve of a test set consisting of a treatment-effective group and a treatment-ineffective group of patients with bipolar disorder based on a random forest model (3 gut microbial markers) according to an embodiment of the present invention Area under AUC.
  • Bipolar disorder is a type of chronic mental illness that has both depressive episodes and manic episodes. It is recurrent. The patient has obstacles in emotional processing and cognitive function, which seriously affects the patient's normal social life And other functions. About 1% of the world's comorbid population is one of the four major causes of adolescent disability, but the pathogenesis has not yet been fully elucidated. The current view is that it is closely related to the interaction between genetics and the environment.
  • Therapeutic effect that is, “therapeutic effect” refers to the effect of treatment of diseases by means of drugs or surgery. It is mainly based on the four-level evaluation criteria, including recovery, marked effect, progress, and ineffectiveness. The “curative effect” in this study mainly refers to "significantly effective” and “ineffective”. Because in the present invention, the treatment of bipolar disorder is a single drug treatment, and whether the change rate of the score of the 17 Hamilton Depression Scale (HDRS-17) scale is ⁇ 50% is used to evaluate the drug treatment for 1 month Is it valid afterwards?
  • HDRS-17 Hamilton Depression Scale
  • Biomarkers are indicators that can be used to determine the cause of a disease, diagnose early, and evaluate the occurrence and development of the disease, or to evaluate the efficacy or safety of drug treatment in the target population. It mainly includes any substances at different biological levels (individuals, cells, molecules) that reflect the specific biological state of the body (such as diseases), such as small molecular substances such as blood sugar for evaluating diabetes, and large molecular substances such as proteins, nucleic acids, and lipids.
  • diseases such as small molecular substances such as blood sugar for evaluating diabetes
  • large molecular substances such as proteins, nucleic acids, and lipids.
  • biomarkers can also be expressed as "intestinal microbes” and "intestinal flora", because the biomarkers related to bipolar disorder discovered in this study are all derived from subjects Stool sample after intestinal metabolism.
  • the biomarker of the present invention uses high-throughput sequencing to batch analyze stool samples of the treatment-effective group and the treatment-ineffective group of patients with bipolar disorder. Based on high-throughput sequencing data, the treatment-effective group and the treatment-ineffective group of patients with bipolar disorder are compared, so as to determine the specific flora related to the prediction of the curative effect of patients with bipolar disorder.
  • Sample collection and processing Collect the stool samples of 62 cases of bipolar disorder, collect the stool samples and distribute them into labeled cryotubes, transport them under freezing conditions and transfer them to -80°C refrigerator for storage for later use.
  • the subject of the present invention is based on inpatient and/or outpatient patients who meet the diagnostic criteria for bipolar disorder in the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR).
  • DSM-IV-TR Diagnostic and Statistical Manual of Mental Disorders
  • the exclusion criteria are: 1) Chronic infection, serious systemic diseases (such as diabetes) and autoimmune diseases; 2) Consumption of antibiotics, probiotics or probiotics within 4 weeks before screening; 3) Current pregnancy, breastfeeding or menstruation Irregular women; 4) History of traumatic brain injury; 5) Contraindications of magnetic resonance imaging (MRI), such as metal implants or claustrophobia.
  • MRI magnetic resonance imaging
  • HDRS-17 17-item Hamilton Depression Scale
  • MADRS Montgomery-Asperger Depression Scale
  • YMRS Youth Mania Scale
  • HDRS-17 score not less than 14 points is set as the threshold for the current depressive episode.
  • the LDA Effect Size (LEfSe) analysis technology was used to analyze the difference in the relative abundance of the flora between the treatment effective group and the treatment ineffective group.
  • the non-parametric factor Kruskal-Wallis rank sum test is used to detect the relative abundance difference between the two groups to obtain significantly different species; 2) Second, use the Wilcoxon rank sum test to detect whether all subspecies of the species with significant differences obtained in the previous step tend to the same classification level; 3) Finally, use linear discriminant analysis (LDA) to reduce the dimensionality and evaluate the data The significant difference in the influence of the flora (ie LDA score) results in the final difference species (refer to the literature: Segata N, et al. Metagenomic biomarker discovery and explanation [J]. Genome Biol, 2011, 12(6): R60.).
  • LDA linear discriminant analysis
  • Figure 1 uses LEFSE and LDA analysis to compare the different flora. Use LDA ⁇ 2 as the threshold for the significance of the difference. The LDA score shows that there is a significant difference in bacteria between the BD patients in the treatment-ineffective group (right part, uneffective) and the treatment effective group (left, effective).
  • the random forest classifier was used to screen potential biomarkers of curative effect prediction during the treatment of bipolar disorder.
  • the treatment of bipolar disorder was constructed.
  • the training set and test set of the gut microbial markers of the effective group and the ineffective group, and the content value of the biomarker of the test set sample to be tested is evaluated.
  • the training set refers to a data set of the content of each biomarker in the samples to be tested for subjects in the effective and ineffective groups of bipolar disorder treatment with a certain number of samples.
  • the present invention selects 27 bipolar disorder patients and 14 healthy people as the training set from 54 samples (35 treatment-effective bipolar disorder patient groups and 19 treatment-ineffective bipolar disorder patient groups). The remaining 13 samples (8 patients with bipolar disorder and 5 healthy people) were used as the test set.
  • the present invention performs five 10-fold cross-validation on the RF classifier ( Figure 2 shows the error rate distribution of the 5-fold 10-fold cross-validation in the random forest classifier).
  • the present invention is based on 5 times of 10-fold cross-validation results, and the RF classifier finally selects 3 optimal biomarker combinations.
  • the detailed information of the relative abundance of microbial markers in the training set is shown in Tables 1-1 and 1-2. Test The detailed relative abundance information of microbial markers in the set is shown in Table 2 below. Table 3 shows the combination of three biomarkers to predict the curative effect probability of the training set).
  • Table 1-1 The relative abundance information of different bacterial groups in the training set
  • Table 3 The accuracy of the training set using the relative abundance information of flora markers to predict the therapeutic effect
  • HSH_104 0.546565 HSH_92 0.714679 HSH_31 0.795832 HSH_96 0.761402 HSH_79 0.922007 s1B1065 0.714679 s1B1008 0.908255 B1072 0.292687 s1B2002 0.893349 B2001 0.306945 s1B1055 0.482749 BP_3 0.295577 B1004 0.609374 BP_6 0.53206 B1066 0.725082 HSH_157 0.292865 B1103 0.910725 HSH_21 0.627038 B1111 0.609374 HSH_27 0.567371 BP_2 0.757439 HSH_76 0.520719 BP_9 0.65124 HSH_88 0.598444 HSH_106 0.76572 HSH_98 0.649793 HSH_109 0.729001 s1B1063 0.707049 HSH_112 0.922245 s1B1094 0.420791 HSH_33 0.65124 s1B2018 0.
  • the results show that the combination of markers obtained from this model can be used as a potential biomarker for predicting the efficacy of treatment of bipolar disorder and that of treatment failure.
  • Table 4 shows the combination of 3 biomarkers to predict the probability of disease in the test set.
  • Table 5 shows the detailed information of the 3 biomarkers.
  • Table 4 The accuracy of predicting the prevalence of the test set using the relative abundance of flora markers
  • the technical means used in the examples are conventional means well known to those skilled in the art, and can be carried out with reference to the third edition of the "Molecular Cloning Experiment Guide” or related products.
  • the reagents and products used are also available. Commercially acquired.
  • the various processes and methods that are not described in detail are conventional methods known in the art.
  • the source of the reagents, trade names, and those that need to list their components are all indicated when they appear for the first time, and the same reagents used thereafter, if there is no special The description is the same as the content indicated for the first time.
  • the present invention adopts the analysis method of metagenomic association analysis (Metagenome-Wide Association Study, MWAS), and analyzes the composition and relative abundance of the fecal samples by sequencing; the Lefse analysis method is used to analyze the effective groups and the groups of patients with bipolar disorder. The difference in the relative abundance of the bacteria in the treatment ineffective group; the random forest discriminant model is used to distinguish between the effective and ineffective groups of bipolar disorder to obtain the disease probability, which can be used to predict and evaluate the efficacy of bipolar disorder or to find potential Drug targets.
  • metagenomic association analysis Methodagenome-Wide Association Study, MWAS
  • MWAS Metagenomic association analysis
  • the sequencing (second-generation sequencing) and MWAS are well-known in the art, and those skilled in the art can make adjustments according to specific conditions. According to the embodiment of the present invention, it can be performed according to the method described in the literature (Jun Wang, and Huijue Jia. Metagenome wide association studies: fine-mining the microbiome. Nature Reviews Microbiology 14.8 (2016): 508-522.).
  • the method of using the random forest model and the ROC curve is well-known in the art, and those skilled in the art can set and adjust the parameters according to specific conditions. According to the embodiment of the present invention, it can be based on the literature (Drogan D, et al. Untargeted Metabolic Profiling Identifies Alter Serum Metabolites of Type 2 Diab etes Melitus in a Prospective, Nested Case Control Study. Clin Chem 2015, 61:487-497 ;) The method described in.
  • a training set of biomarkers of subjects in the treatment-effective group and the treatment-ineffective group of patients with bipolar disorder is constructed, and on this basis, the biomarker content value of the sample to be tested is evaluated.
  • biomarkers are the intestinal flora present in the human body.
  • the subject's intestinal flora is associated with the analysis, and it is obtained that the biomarkers of the bipolar disorder population show a certain content range value in the flora detection.
  • biomarker disclosed in the present invention has high accuracy and specificity, and provides a basis for predicting the therapeutic effect of bipolar disorder and searching for potential drug targets.
  • the biomarker combination for bipolar disorder based on the intestinal flora is used as a detection target or a detection target in the preparation of a detection kit.
  • biomarker combination based on the intestinal flora-based treatment efficacy of bipolar disorder as a target in predictive treatment.

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Abstract

L'invention concerne des biomarqueurs à base de microbes intestinaux pour prédire un effet curatif sur un trouble bipolaire, et le criblage et des applications de ceux-ci. Un biomarqueur 1), c'est-à-dire Eubacterium_biforme, un biomarqueur 2), c'est-à-dire des Ruminococcus_torques et un biomarqueur 3), c'est-à-dire, Collinsella_non classée, sont compris et l'abondance relative d'une combinaison des biomarqueurs dans un groupe efficace pour le traitement de patients atteints d'un trouble bipolaire est significativement augmentée. L'invention concerne également une application des biomarqueurs en tant que cibles de test ou objets de test dans la préparation d'un kit de test, et une application des biomarqueurs en tant que cibles dans une prédiction d'effet curatif.
PCT/CN2020/081945 2020-03-18 2020-03-28 Biomarqueurs à base de microbes intestinaux pour prédire un effet curatif sur un trouble bipolaire, et criblage et applications de ceux-ci WO2021184413A1 (fr)

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